Understanding agentic AI: Revolutionize your business operations 

The rapid development of the artificial intelligence (AI) landscape is not slowing down. Generative AI revolutionized content creation and now agentic AI expands on these capabilities – creating a level of autonomy AI agents have never had before. This groundbreaking advancement will fundamentally change the way companies operate as it continues to push the limits of AI’s current capabilities.

What is agentic AI?

Agentic AI is the next evolution of AI. Building upon the foundation of traditional AI, rule-based AI that relies on historical data to make decisions, and generative AI, which creates new content using natural language processing (NPL) and other advanced technologies, agentic AI takes things a step further by enabling interactive, autonomous agents that can perform complex tasks and adjust to anomalies in real-time without the need for human intervention.

At its core, agentic AI relies on large language models (LLMs) and machine learning algorithms that are trained on vast amounts of data with data pipelines continuously feeding the AI system with new data to ensure the agents remain up to date with the latest information.

To facilitate real-time interactions, agentic AI systems utilize NPL techniques that enable the agents to understand and generate human-like responses while improving the agents’ performance over time by learning from past interactions and feedback. Being able to understand and respond to natural language inputs makes agentic AI agents highly versatile and capable of adapting to various scenarios.

Agentic AI is not just an incremental improvement over its predecessors; it’s a transformative technology that build upon the aspects of traditional and generative AI to interact with users in a more human-like manner.

How can companies use agentic AI?

Companies can leverage agentic AI in numerous ways to enhance operational efficiency and improve customer experiences. For example, in customer service, agentic AI can streamline interactions by autonomously handling customer inquiries, reducing response times.

Consider a scenario where a customer needs to return a product. Instead of navigating through a complex phone menu and waiting for a human representative, the customer can instead interact with an AI agent that quickly processes the return, offers alternative products or even provides a discount for the inconvenience. This level of service not only enhances customer satisfaction but also reduces the need for human intervention, allowing companies to re-allocate staff to more value-added activities.

Supply chain management is another area where agentic AI can make a substantial impact. By continuously monitoring inventory levels, product demand forecasts and external factors such as weather patterns, AI agents can make real time adjustments to ensure that products are available where and when they are needed. This proactive approach to autonomously managing tasks such as order processing, inventory balancing and demand prediction makes agentic AI a valuable asset for companies looking to improve operational efficiency.

Requirements for a successful implementation

When implementing agentic AI, companies need to focus on three critical areas: data, infrastructure and talent. First, having high-quality, well-governed data is essential, as the accuracy of AI outputs depends on the quality of the input data. Strong data management with the right datasets, strategy, controls, security and governance are integral both to ensure high quality data but also certify safe data usage and compliance with regulatory frameworks.

Second, robust infrastructure is necessary to support the computational demands of the LLMs that power agentic AI agents. This includes having the right hardware and software in-place to handle complex tasks efficiently and ensure a safe environment for AI deployment and usage.

Finally, training employees with AI technologies is crucial. Companies need to ensure their workforce is equipped with the skills to manage and interact with AI systems effectively and responsibly. Leveraging effective change management practices can help to enhance data and AI literacy and foster understanding in your workforce, ensuring universal understanding of how to leverage the new technology to become more efficient and innovative in their daily work.

Deploying agentic AI and seeing positive return on investment (ROI) requires demonstrated strength in these critical areas along with an overarching vision that’s in alignment with your organizational strategy and clearly defines the purpose behind the initiative. Companies should consider starting with small, manageable use cases to build trust and demonstrate the value of agentic AI. For example, automating email administration or customer service tasks can provide immediate benefits and help companies understand the potential of AI. As trust in the technology grows, companies can expand its use to more complex areas.

Potential challenges and future prospects

While the potential benefits of agentic AI agents are immense, there are also challenges that companies must address. One of the primary concerns is the trustworthiness of AI agents. Companies need to ensure that these agents can perform tasks with the same rigor and accuracy as human employees. This requires extensive testing and validation to build confidence in the technology.

Another challenge stems from the integration of agentic AI with existing systems and processes. Companies need to carefully plan and execute the deployment of agentic AI agents to avoid disruptions and ensure seamless operations. This may involve upgrading infrastructure, retraining staff or reengineering workflows to accommodate the new technology.

Looking ahead, the future of agentic AI is promising. As the technology continues to evolve, one can expect to see even more sophisticated AI agents capable of handling increasingly complex tasks, offering even greater opportunities for innovation and efficiency in various industries and revolutionizing how businesses operate.

How we can help

By focusing on high-quality data, robust infrastructure and employee training, companies can successfully implement agentic AI and unlock its full potential – embracing AI to stay competitive in the current market.

Baker Tilly’s digital solutions team can help you get the right data and infrastructure in place, while ensuring your people are trained to effectively utilize incoming AI technologies. Our AI workshop can help your company outline AI use cases and begin to develop a strategy for successful implementation.

Interested in getting started with AI? Contact one of our professionals to learn more.